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全身参数化PATLAK [F]-FDG PET/CT中代谢率和分布容积定量的变异性:一项针对肺癌患者的前瞻性试验

Variability of Metabolic Rate and Distribution Volume Quantification in Whole-Body Parametric PATLAK [F]-FDG PET/CT-A Prospective Trial in Patients with Lung Cancer.

作者信息

Ursprung Stephan, Zender Lars, Ghibes Patrick, Hagen Florian, Nikolaou Konstantin, la Fougère Christian, Weissinger Matthias

机构信息

Department of Diagnostic and Interventional Radiology, University Hospital Tuebingen, 72076 Tuebingen, Germany.

Department of Medical Oncology and Pneumology (Internal Medicine VIII), University Hospital Tuebingen, 72076 Tuebingen, Germany.

出版信息

Diagnostics (Basel). 2025 Jul 5;15(13):1719. doi: 10.3390/diagnostics15131719.

DOI:10.3390/diagnostics15131719
PMID:40647718
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC12249058/
Abstract

: The recent introduction of whole-body positron emission tomography/ computed tomography (PET/CT) scanners and multi-bed, multi-time point acquisition technique enable calculating fluorodeoxyglucose (FDG) kinetics in the whole body. However, validating parametric, Patlak-derived data is difficult on phantoms. : This prospective study investigated the effect of quantification methods mean, max, and peak on the metabolic rate (MR-FDG) and distribution volume (DV-FDG) quantification, as well as the diagnostic accuracy of parametric Patlak FDG-PET scans in diagnosing lung lesions and lymph node metastases, using histopathology and follow-up as reference standards. Dynamic whole-body FDG PET was acquired for 80 minutes in 34 patients with indeterminate lung lesions and kinetic parameters extracted from lung lesions and representative mediastinal and hilar lymph nodes. : All quantification methods-mean, max, and peak-demonstrated high diagnostic accuracy (AUC: MR-FDG: 0.987-0.991 and 0.893-0.905; DV-FDG: 0.948-0.975 and 0.812-0.825) for differentiating benign from malignant lymph nodes and lung lesions. Differences in the magnitude of MR-FDG (-4.76-14.09) and DV-FDG (-10.64-46.10%) were substantial across methods. Variability was more pronounced in lymph nodes (MR-FDG: 1.37-3.48) than in lung lesions (MR-FDG: 3.31-5.04). The variability was lowest between mean and max quantification, with percentage differences of 40.87 ± 5.69% for MR-FDG and 39.26 ± 7.68% for DV-FDG. : The choice of method to measure MR-FDG and DV-FDG greatly influences the results, especially in smaller lesions with large and systematic differences. For lung lesions, a conversion factor between mean and max methods of 40% provides acceptable agreement, facilitating retrospective comparisons of measurements, e.g., in meta-analyses.

摘要

近期全身正电子发射断层扫描/计算机断层扫描(PET/CT)扫描仪以及多床位、多时间点采集技术的引入,使得能够在全身范围内计算氟脱氧葡萄糖(FDG)动力学。然而,在体模上验证基于Patlak的参数数据具有难度。

这项前瞻性研究使用组织病理学和随访作为参考标准,调查了均值、最大值和峰值等量化方法对代谢率(MR-FDG)和分布容积(DV-FDG)量化的影响,以及参数化Patlak FDG-PET扫描在诊断肺部病变和淋巴结转移方面的诊断准确性。对34例肺部病变性质不明的患者进行了80分钟的动态全身FDG PET扫描,并从肺部病变以及具有代表性的纵隔和肺门淋巴结中提取动力学参数。

所有量化方法——均值、最大值和峰值——在区分良性与恶性淋巴结及肺部病变方面均显示出较高的诊断准确性(AUC:MR-FDG:0.987 - 0.991和0.893 - 0.905;DV-FDG:0.948 - 0.975和0.812 - 0.825)。不同方法之间MR-FDG(-4.76 - 14.09)和DV-FDG(-10.64 - 46.10%)的大小差异很大。淋巴结中的变异性(MR-FDG:1.37 - 3.48)比肺部病变中的变异性(MR-FDG:3.31 - 5.04)更为明显。均值和最大值量化之间的变异性最低,MR-FDG的百分比差异为40.87 ± 5.69%,DV-FDG的百分比差异为39.26 ± 7.68%。

测量MR-FDG和DV-FDG的方法选择对结果有很大影响,尤其是在差异较大且具有系统性差异的较小病变中。对于肺部病变,均值和最大值方法之间40%的转换因子可提供可接受的一致性,便于进行测量的回顾性比较,例如在荟萃分析中。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5b6c/12249058/3a1f61206888/diagnostics-15-01719-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5b6c/12249058/52d14eb40fb8/diagnostics-15-01719-g0A1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5b6c/12249058/6ce9a61f26db/diagnostics-15-01719-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5b6c/12249058/5e5e6a2d3cda/diagnostics-15-01719-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5b6c/12249058/8541aeeeed8f/diagnostics-15-01719-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5b6c/12249058/f98d7b3a1ca7/diagnostics-15-01719-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5b6c/12249058/3a1f61206888/diagnostics-15-01719-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5b6c/12249058/52d14eb40fb8/diagnostics-15-01719-g0A1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5b6c/12249058/6ce9a61f26db/diagnostics-15-01719-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5b6c/12249058/5e5e6a2d3cda/diagnostics-15-01719-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5b6c/12249058/8541aeeeed8f/diagnostics-15-01719-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5b6c/12249058/f98d7b3a1ca7/diagnostics-15-01719-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5b6c/12249058/3a1f61206888/diagnostics-15-01719-g005.jpg

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